Keywords: pyrolysis bio-oils, molecular reconstruction, kinetic Monte Carlo
Description
Fast pyrolysis is one of the thermo-chemical conversion routes that allow to directly transform solid lignocellulosic biomass into liquid products. The resulting bio-oils require, however, a dedicated pre-refining step to eliminate their high levels of oxygen. One promising route consists in a specific treatment of the bio-oils in the presence of hydrogen. To develop a dedicated hydrotreating process for bio-oils, the knowledge of the chemical composition of the fast pyrolysis bio-oils and the kinetic modeling of the various reaction steps in the hydrotreating process are essential. The aim of this PhD thesis is therefore to understand the structure, composition and reactivity of the various bio-oil compounds through modeling of pre-existing experimental data.
Fast pyrolysis bio-oils are extremely complex organic mixtures. In parallel to the on-going analytical developments, molecular reconstruction techniques (composition modeling step) judiciously recombine various analytical inputs to generate a representative synthetic mixture of molecules whose properties are consistent with the bio-oil’s properties. In order to subsequently model the various reaction steps occurring during the hydrotreating of bio-oils (reaction modeling step), one not only needs to have a detailed characterization of the bio-oil feed, but a detailed description of the various transformations is also required. In such a case, the use of a stochastic simulation algorithm, developed to simulate complex reaction systems, avoids the a priori generation of the entire reaction network by defining and using a limited number of reaction classes and reaction rules on the fly. This not only allows to identify the main reaction pathways, but also to retain the molecular information along the entire simulation, thereby resulting in a molecular description of the effluent and hence acquiring a more fundamental insight in these complex processes.
Nr of positions available : 1
Research Fields
Engineering - Chemical engineering
Career Stage
Early stage researcher or 0-4 yrs (Post graduate)
Research Profiles
First Stage Researcher (R1)
Benefits
IFPEN offers a stimulating research environment, with access to first in class laboratory infrastructures and computing facilities. IFPEN offers competitive salary and benefits packages (amongst which 30 vacation days). All PhD students have access to dedicated seminars and training sessions.
Comment/web site for additional job details
Additional details: theses.ifpen.fr/jcms/r_8284/en/2015-phd-subjects
Contact: jan.verstraete@ifpen.fr
Requirements
| Engineering |
| Knowledge of basic organic chemistry, numerical calculus and informatics is highly appreciated. |
| Master Degree or equivalent |